Using statistical models to characterize eco-driving style with an aggregated indicator

Andrieu, Cindie; Pierre, Guillaume Saint

doi:10.1109/ivs.2012.6232197

Cited by 24 publications

(18 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…They relied on data, such as vehicle speed, acceleration, altitude, GPS, throttle position, instant fuel consumption and the engine rotations. Andrieu and Pierre [66] developed an efficient Ecological Driving Assistance System (EDAS) aiming to detect eco-driving behavior and provide drivers with recommendations to help them to reduce the fuel consumption and preserve their safety. They used the CAN and OBD to monitor driving parameters, for instance, vehicle speed, RPM, fuel, brake pedal and throttle position.…”

Section: A Intra-vehicular Sensormentioning

confidence: 99%

“…Relying on visual information, Kumtepe et al [42] developed a method to detect the driver's aggressiveness by detecting lane deviation and collision time. Andrieu and Pierre [66] employed a GPS, front car camera and a fuel flow meter to develop an efficient EDAS. They also used a specific fuel flow hardware aiming to validate the fuel consumption provided by an OBD port.…”

Section: A Intra-vehicular Sensormentioning

confidence: 99%

See 1 more Smart Citation

Vehicular Data Space: The Data Point of View

Rettore

Maia

Villas

et al. 2019

IEEE Commun. Surv. Tutorials

View full text Add to dashboard Cite

Over the years, governments and automakers launched initiatives to improve road traffic efficiency, safety, and people mobility. They have been working on various aspects of intelligent transportation systems (ITSs), which aim to improve decision-making, availability of information, and communication technologies to provide applications and services to boost the transportation systems. The development of new applications and services for ITS depends on the availability of different data sources, what it is not the current case. Many studies focus on the communication issues of applications and their associated challenges. To reveal the recent vehicular data use, we examined the most remarkable studies of the last few years, which describe services and applications for ITS, however with a focus on the data employed by them. We introduce the concept of vehicular data space (VDS), which is then used to describe the vehicular scenario from the perspective of data. Moreover, we outline a taxonomy, according to the different data sources. We also categorize the applications, highlighting the data each one used in their approach. Finally, we present some challenges and open issues related to the process for data creation, data preparation, data processing, and data use. In a nutshell, this paper constitutes one of the first holistic surveys on services and applications for ITSs, focusing on the data used by them, as well as their future challenges. Index Terms-Vehicular data space (VDS), vehicular sensor data, connected vehicles, intelligent transportation system (ITS), heterogeneous data, vehicular ad-hoc network (VANET). I. INTRODUCTIONM ORE and more cities will have to deal with significant issues related to transportation and traffic because people and goods are in constant need for quicker and safer mobility modes. The number of fatalities and injuries on the road has achieved an alarming scenario. Globally, 1.3 million people die every year, and up to 50 million suffer severe injuries. These facts have a direct impact on the economics of nations, leading to costs in the order of about 2% to 5% of the Gross Domestic Product (GDP) in many countries [1]. It is also reported that traffic congestion results in critical economic and environmental costs. In 2011, 498 U.S. urban areas were

show abstract

Section: A Intra-vehicular Sensormentioning

confidence: 99%

Section: A Intra-vehicular Sensormentioning

confidence: 99%

Vehicular Data Space: The Data Point of View

Rettore

Maia

Villas

et al. 2019

IEEE Commun. Surv. Tutorials

View full text Add to dashboard Cite

show abstract

“…2 for a distance greater than 500 meters). Therefore, an adaptive weighting of cost terms (12) and (13) in form of discretization independent tradeoff parameters is introduced in Sections III-B and III-C. For a distance independent weighting of the desired velocity, the idea of [16] is picked up, where stationary driving with conditions α k = 0, ΔE kin,k = 0, and ΔE eng,k = 0 for all k…”

Section: B Discretization Independent Velocity Weightingmentioning

confidence: 99%

“…The first group is calculating hints based on generic rules of eco-driving. Without numerical optimization, but using heuristics defined by experts, such driver supporting approaches yield good results [12], [13]. The second category is predictive highway driving using horizon optimization in an MPC.…”

Section: Introductionmentioning

confidence: 99%

Inhomogeneous Model Predictive Control Horizon Discretization for an Urban Truck Energy Efficient Driving Application

Henzler

Buchholz

Dietmeyer

2015

2015 IEEE 18th International Conference on Intelligent Transportation Systems

View full text Add to dashboard Cite

This paper presents a novel approach on Model Predictive Control (MPC) using an inhomogeneously discretized preview horizon for the application of urban energy efficient driving. One solution for model predictive energy efficient driving is a direct solution of the underlying speed profile optimization problem using Quadratic Programming (QP), which allows computationally efficient and robust results. Our inhomogeneous horizon discretization allows to have a finer discretization of the typically important near future and a wider discretization of the less decisive far range of an MPC, while keeping a long preview horizon and at the same time limit the number of supporting points, hence limit the problem dimension, computational complexity, and proportional execution time. In extensive simulations of a real-world urban driving scenario, we demonstrate a significantly improved control performance in terms of fuel consumption, trip time, or constraint violation for the same computational complexity.

show abstract

“…This system can increase the driving safety as well as decrease the air pollution and unnecessary fuel consumption caused by vehicle faults. The authors in [57] present the construction of an aggregated indicator of a fuel-efficient driving style. Depending on some driving indicators, the estimated probability of being an eco-driver is used as an eco-index to characterize that driving pattern.…”

Section: The Eco-driving Assist Systemmentioning

confidence: 99%

Eco-Driving --- Current Strategies and issues, A Preliminary Survey

Ni²,

Ding³

2015

Proceedings of the 2015 Information Technology and Mechatronics Engineering Conference

View full text Add to dashboard Cite

After safe driving, eco-driving has become an economic and green driving idea, which is adapted to the modern engine technology and typically consists of changing a person's driving behavior based on general advice to drivers, such as accelerating slowly, driving smoothly, etc. The concept of eco-driving can help save energy and reduce pollution emissions in an efficient way. In this article, a comprehensive preliminary overview of state-of-art research on this issue is presented in several parts: methods for emission estimation, traffic signal control, cruise control, and eco-driving assist systems. Besides, the challenges and opportunities associated with eco-driving are discussed as well.

show abstract

Using statistical models to characterize eco-driving style with an aggregated indicator

Cited by 24 publications

References 9 publications

Vehicular Data Space: The Data Point of View

Vehicular Data Space: The Data Point of View

Inhomogeneous Model Predictive Control Horizon Discretization for an Urban Truck Energy Efficient Driving Application

Eco-Driving --- Current Strategies and issues, A Preliminary Survey

Contact Info

Product

Resources

About